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Extracting Quantal Properties of Transmission at Central Synapses

  • Frederic Lanore
  • R. Angus SilverEmail author
Protocol
Part of the Neuromethods book series (NM, volume 113)

Abstract

Chemical synapses enable neurons to communicate rapidly, process and filter signals and to store information. However, studying their functional properties is difficult because synaptic connections typically consist of multiple synaptic contacts that release vesicles stochastically and exhibit time-dependent behavior. Moreover, most central synapses are small and inaccessible to direct measurements. Estimation of synaptic properties from postsynaptic currents or potentials is complicated by the presence of nonuniform release probability and nonuniform quantal properties. The presence of multivesicular release and postsynaptic receptor saturation at some synapses can also complicate the interpretation of quantal parameters. Multiple-probability fluctuation analysis (MPFA; also known as variance-mean analysis) is a method that has been developed for estimating synaptic parameters from the variance and mean amplitude of synaptic responses recorded at different release probabilities. This statistical approach, which incorporates nonuniform synaptic properties, has become widely used for studying synaptic transmission. In this chapter, we describe the statistical models used to extract quantal parameters and discuss their interpretation when applying MPFA.

Key words

Synapse Vesicle Active zone Release probability Release site Quantal analysis MPFA Variance-mean analysis 

Notes

Acknowledgements

We thank Antoine Valera for comments on the manuscript. FL is supported by an IEF Marie Curie fellowship (FP7) and RAS holds a Wellcome Trust Principal Research Fellowship and an ERC Advanced Grant.

References

  1. 1.
    Fatt P, Katz B (1952) Spontaneous subthreshold activity at motor nerve endings. J Physiol 117:109–128PubMedPubMedCentralGoogle Scholar
  2. 2.
    del Castillo J, Katz B (1954) Quantal components of the end-plate potential. J Physiol 124:560–573CrossRefPubMedCentralGoogle Scholar
  3. 3.
    Fatt P, Katz B (1950) Some observations on biological noise. Nature 166:597–598CrossRefPubMedGoogle Scholar
  4. 4.
    De Robertis E, Bennett HS (1955) Some features of the submicroscopic morphology of synapses in frog and earthworm. J Biophys Biochem Cytol 1:47CrossRefPubMedCentralGoogle Scholar
  5. 5.
    Katz B (1969) The release of neural transmitter substances. Liverpool University Press, LiverpoolGoogle Scholar
  6. 6.
    Kuno M (1964) Quantal components of excitatory synaptic potentials in spinal motoneurones. J Physiol 175:81–99CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Malinow R, Tsien RW (1990) Presynaptic enhancement shown by whole-cell recordings of long-term potentiation in hippocampal slices. Nature 346:177–180CrossRefPubMedGoogle Scholar
  8. 8.
    Bekkers JM, Stevens CF (1990) Presynaptic mechanism for long-term potentiation in the hippocampus. Nature 346:724–729CrossRefPubMedGoogle Scholar
  9. 9.
    Larkman A, Stratford K, Jack J (1991) Quantal analysis of excitatory synaptic action and depression in hippocampal slices. Nature 350:344–347CrossRefPubMedGoogle Scholar
  10. 10.
    Edwards F (1991) Neurobiology. LTP is a long term problem. Nature 350:271–272CrossRefPubMedGoogle Scholar
  11. 11.
    Kullmann DM, Nicoll RA (1992) Long-term potentiation is associated with increases in quantal content and quantal amplitude. Nature 357:240–244CrossRefPubMedGoogle Scholar
  12. 12.
    Walmsley B, Edwards FR, Tracey DJ (1988) Nonuniform release probabilities underlie quantal synaptic transmission at a mammalian excitatory central synapse. J Neurophysiol 60:889–908PubMedGoogle Scholar
  13. 13.
    Rosenmund C, Clements JD, Westbrook GL (1993) Nonuniform probability of glutamate release at a hippocampal synapse. Science 262:754–757CrossRefPubMedGoogle Scholar
  14. 14.
    Walmsley B (1995) Interpretation of “quantal” peaks in distributions of evoked synaptic transmission at central synapses. Proc Biol Sci 261:245–250CrossRefPubMedGoogle Scholar
  15. 15.
    Sigworth FJ (1980) The variance of sodium current fluctuations at the node of Ranvier. J Physiol 307:97–129CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Traynelis SF, Silver RA, Cull-Candy SG (1993) Estimated conductance of glutamate receptor channels activated during EPSCs at the cerebellar mossy fiber-granule cell synapse. Neuron 11:279–289CrossRefPubMedGoogle Scholar
  17. 17.
    Silver RA, Cull-Candy SG, Takahashi T (1996) Non-NMDA glutamate receptor occupancy and open probability at a rat cerebellar synapse with single and multiple release sites. J Physiol 494(Pt 1):231–250CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Silver RA, Momiyama A, Cull-Candy SG (1998) Locus of frequency-dependent depression identified with multiple-probability fluctuation analysis at rat climbing fibre-Purkinje cell synapses. J Physiol 510(Pt 3):881–902CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Reid CA, Clements JD (1999) Postsynaptic expression of long-term potentiation in the rat dentate gyrus demonstrated by variance-mean analysis. J Physiol 518(Pt 1):121–130CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Clements JD, Silver RA (2000) Unveiling synaptic plasticity: a new graphical and analytical approach. Trends Neurosci 23:105–113CrossRefPubMedGoogle Scholar
  21. 21.
    Clamann HP, Mathis J, Lüscher HR (1989) Variance analysis of excitatory postsynaptic potentials in cat spinal motoneurons during posttetanic potentiation. J Neurophysiol 61:403–416PubMedGoogle Scholar
  22. 22.
    Sargent PB, Saviane C, Nielsen TA et al (2005) Rapid vesicular release, quantal variability, and spillover contribute to the precision and reliability of transmission at a glomerular synapse. J Neurosci 25:8173–8187CrossRefPubMedGoogle Scholar
  23. 23.
    Lanore F, Labrousse VF, Szabo Z et al (2012) Deficits in morphofunctional maturation of hippocampal mossy fiber synapses in a mouse model of intellectual disability. J Neurosci 32:17882–17893CrossRefPubMedGoogle Scholar
  24. 24.
    Meyer AC, Neher E, Schneggenburger R (2001) Estimation of quantal size and number of functional active zones at the calyx of held synapse by nonstationary EPSC variance analysis. J Neurosci 21:7889–7900PubMedGoogle Scholar
  25. 25.
    Saviane C, Silver RA (2006) Fast vesicle reloading and a large pool sustain high bandwidth transmission at a central synapse. Nature 439:983–987CrossRefPubMedGoogle Scholar
  26. 26.
    Hallermann S, Fejtova A, Schmidt H et al (2010) Bassoon speeds vesicle reloading at a central excitatory synapse. Neuron 68:710–723CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Scheuss V, Neher E (2001) Estimating synaptic parameters from mean, variance, and covariance in trains of synaptic responses. Biophys J 81:1970–1989CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Neher E, Sakaba T (2003) Combining deconvolution and fluctuation analysis to determine quantal parameters and release rates. J Neurosci Methods 130:143–157CrossRefPubMedGoogle Scholar
  29. 29.
    Oleskevich S, Clements J, Walmsley B (2000) Release probability modulates short-term plasticity at a rat giant terminal. J Physiol 524(Pt 2):513–523CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Biró AA, Holderith NB, Nusser Z (2005) Quantal size is independent of the release probability at hippocampal excitatory synapses. J Neurosci 25:223–232CrossRefPubMedGoogle Scholar
  31. 31.
    Biró AA, Holderith NB, Nusser Z (2006) Release probability-dependent scaling of the postsynaptic responses at single hippocampal GABAergic synapses. J Neurosci 26:12487–12496CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Humeau Y, Doussau F, Popoff MR et al (2007) Fast changes in the functional status of release sites during short-term plasticity: involvement of a frequency-dependent bypass of Rac at Aplysia synapses. J Physiol 583:983–1004CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Valera AM, Doussau F, Poulain B et al (2012) Adaptation of granule cell to purkinje cell synapses to high-frequency transmission. J Neurosci 32:3267–3280CrossRefPubMedGoogle Scholar
  34. 34.
    Sola E, Prestori F, Rossi P et al (2004) Increased neurotransmitter release during long-term potentiation at mossy fibre-granule cell synapses in rat cerebellum. J Physiol 557:843–861CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Fourcaudot E, Gambino F, Humeau Y et al (2008) cAMP/PKA signaling and RIM1alpha mediate presynaptic LTP in the lateral amygdala. Proc Natl Acad Sci 105:15130–15135CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Murthy VN, Sejnowski TJ, Stevens CF (1997) Heterogeneous release properties of visualized individual hippocampal synapses. Neuron 18:599–612CrossRefPubMedGoogle Scholar
  37. 37.
    Bekkers JM, Richerson GB, Stevens CF (1990) Origin of variability in quantal size in cultured hippocampal neurons and hippocampal slices. Proc Natl Acad Sci 87:5359–5362CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Silver RA, Traynelis SF, Cull-Candy SG (1992) Rapid-time-course miniature and evoked excitatory currents at cerebellar synapses in situ. Nature 355:163–166CrossRefPubMedGoogle Scholar
  39. 39.
    Frerking M, Wilson M (1996) Effects of variance in mini amplitude on stimulus-evoked release: a comparison of two models. Biophys J 70:2078–2091CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Borst JG, Lodder JC, Kits KS (1994) Large amplitude variability of GABAergic IPSCs in melanotrophs from Xenopus laevis: evidence that quantal size differs between synapses. J Neurophysiol 71:639–655PubMedGoogle Scholar
  41. 41.
    Silver RA (2003) Estimation of nonuniform quantal parameters with multiple-probability fluctuation analysis: theory, application and limitations. J Neurosci Methods 130:127–141CrossRefPubMedGoogle Scholar
  42. 42.
    Branco T, Staras K, Darcy KJ et al (2008) Local dendritic activity sets release probability at hippocampal synapses. Neuron 59:475–485CrossRefPubMedGoogle Scholar
  43. 43.
    Holderith N, Lörincz A, Katona G et al (2012) Release probability of hippocampal glutamatergic terminals scales with the size of the active zone. Nat Neurosci 15:988–997CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Wadiche JI, Jahr CE (2001) Multivesicular release at climbing fiber-Purkinje cell synapses. Neuron 32:301–313CrossRefPubMedGoogle Scholar
  45. 45.
    Christie JM, Jahr CE (2006) Multivesicular release at Schaffer collateral-CA1 hippocampal synapses. J Neurosci 26:210–216CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Foster KA, Regehr WG (2004) Variance-mean analysis in the presence of a rapid antagonist indicates vesicle depletion underlies depression at the climbing fiber synapse. Neuron 43:119–131CrossRefPubMedGoogle Scholar
  47. 47.
    DiGregorio DA, Nusser Z, Silver RA (2002) Spillover of glutamate onto synaptic AMPA receptors enhances fast transmission at a cerebellar synapse. Neuron 35:521–533CrossRefPubMedGoogle Scholar
  48. 48.
    Barbour B, Hausser M (1997) Intersynaptic diffusion of neurotransmitter. Trends Neurosci 20:377–384CrossRefPubMedGoogle Scholar
  49. 49.
    Sakaba T, Schneggenburger R, Neher E (2002) Estimation of quantal parameters at the calyx of Held synapse. Neurosci Res 44:343–356CrossRefPubMedGoogle Scholar
  50. 50.
    Minneci F, Kanichay RT, Silver RA (2012) Estimation of the time course of neurotransmitter release at central synapses from the first latency of postsynaptic currents. J Neurosci Methods 205:49–64CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Vere Jones D (1966) Simple stochastic models for the release of quanta of transmitter from a nerve terminal. Aust J Stat 8:53–63CrossRefGoogle Scholar
  52. 52.
    Quastel DM (1997) The binomial model in fluctuation analysis of quantal neurotransmitter release. Biophys J 72:728–753CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Wong AYC, Graham BP, Billups B et al (2003) Distinguishing between presynaptic and postsynaptic mechanisms of short-term depression during action potential trains. J Neurosci 23:4868–4877PubMedGoogle Scholar
  54. 54.
    Spruston N, Jaffe DB, Williams SH et al (1993) Voltage- and space-clamp errors associated with the measurement of electrotonically remote synaptic events. J Neurophysiol 70:781–802PubMedGoogle Scholar
  55. 55.
    Bar-Yehuda D, Korngreen A (2008) Space-clamp problems when voltage clamping neurons expressing voltage-gated conductances. J Neurophysiol 99:1127–1136CrossRefPubMedGoogle Scholar
  56. 56.
    Silver RA, Lubke J, Sakmann B et al (2003) High-probability uniquantal transmission at excitatory synapses in barrel cortex. Science 302:1981–1984CrossRefPubMedGoogle Scholar
  57. 57.
    Nyquist H (1928) Certain topics in telegraph transmission theory. Trans AIEE 47:617–644Google Scholar
  58. 58.
    Saviane C, Silver RA (2006) Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis. J Neurosci Methods 153:250–260CrossRefPubMedGoogle Scholar
  59. 59.
    Redman S (1990) Quantal analysis of synaptic potentials in neurons of the central nervous system. Physiol Rev 70:165–198PubMedGoogle Scholar
  60. 60.
    Stricker C, Field AC, Redman SJ (1996) Statistical analysis of amplitude fluctuations in EPSCs evoked in rat CA1 pyramidal neurones in vitro. J Physiol 490(Pt 2):419–441CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Tsodyks M, Pawelzik K, Markram H (1998) Neural networks with dynamic synapses. Neural Comput 10:821–835CrossRefPubMedGoogle Scholar
  62. 62.
    Scheuss V, Neher E, Schneggenburger R (2002) Separation of presynaptic and postsynaptic contributions to depression by covariance analysis of successive EPSCs at the calyx of held synapse. J Neurosci 22:728–739PubMedGoogle Scholar
  63. 63.
    Sakaba T, Neher E (2001) Quantitative relationship between transmitter release and calcium current at the calyx of held synapse. J Neurosci 21:462–476PubMedGoogle Scholar
  64. 64.
    Saviane C, Silver RA (2007) Estimation of quantal parameters with multiple-probability fluctuation analysis. Methods Mol Biol 403:303–317CrossRefPubMedGoogle Scholar
  65. 65.
    Turner DA, West M (1993) Bayesian analysis of mixtures applied to post-synaptic potential fluctuations. J Neurosci Methods 47:1–21CrossRefPubMedGoogle Scholar
  66. 66.
    Bhumbra GS, Beato M (2013) Reliable evaluation of the quantal determinants of synaptic efficacy using Bayesian analysis. J Neurophysiol 109:603–620CrossRefPubMedGoogle Scholar
  67. 67.
    Oertner TG, Sabatini BL, Nimchinsky EA et al (2002) Facilitation at single synapses probed with optical quantal analysis. Nat Neurosci 5:657–664PubMedGoogle Scholar
  68. 68.
    Yuste R, Majewska A, Cash SS et al (1999) Mechanisms of calcium influx into hippocampal spines: heterogeneity among spines, coincidence detection by NMDA receptors, and optical quantal analysis. J Neurosci 19:1976–1987PubMedGoogle Scholar
  69. 69.
    Emptage NJ, Reid CA, Fine A et al (2003) Optical quantal analysis reveals a presynaptic component of LTP at hippocampal Schaffer-associational synapses. Neuron 38:797–804CrossRefPubMedGoogle Scholar
  70. 70.
    Sylantyev S, Jensen TP, Ross RA et al (2013) Cannabinoid- and lysophosphatidylinositol-sensitive receptor GPR55 boosts neurotransmitter release at central synapses. Proc Natl Acad Sci 110:5193–5198CrossRefPubMedPubMedCentralGoogle Scholar
  71. 71.
    Marvin JS, Borghuis BG, Tian L et al (2013) An optimized fluorescent probe for visualizing glutamate neurotransmission. Nat Methods 10:162–170CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Kirkby PA, Srinivas Nadella KMN, Silver RA (2010) A compact acousto-optic lens for 2D and 3D femtosecond based 2-photon microscopy. Opt Express 18:13721–13745CrossRefPubMedPubMedCentralGoogle Scholar
  73. 73.
    Fernández-Alfonso T, Nadella KMNS, Iacaruso MF et al (2014) Monitoring synaptic and neuronal activity in 3D with synthetic and genetic indicators using a compact acousto-optic lens two-photon microscope. J Neurosci Methods 222:69–81CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    Rothman JS, Silver RA (2014) Data-driven modeling of synaptic transmission and integration. Prog Mol Biol Transl Sci 123:305–350CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Neuroscience, Physiology and PharmacologyUniversity College LondonLondonUK

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